Open to opportunities

Deepak baraskar

@deepakbaraskar

India

Message

What I'm looking for

I'm seeking opportunities in data science, analytics, software development, testing, QA, and broader IT domains where I can apply Python, SQL, machine learning, and dashboarding skills while continuing to learn.

Results-driven Data Analyst with hands-on experience in data analysis, business intelligence, reporting automation, dashboard development, and predictive analytics. Currently working at Cognizant Technology Solutions, where I leverage SQL, Python, Power BI, and Excel to transform complex datasets into actionable business insights.

Skilled in data cleaning, transformation, ETL processes, KPI reporting, data visualization, statistical analysis, and stakeholder communication. Experienced in developing interactive dashboards, automating reporting workflows, and supporting data-driven decision-making across business functions.

Proficient in SQL, Python, Power BI, Excel, Machine Learning, Data Modeling, Business Analytics, and Performance Reporting. Passionate about solving business problems through data and continuously learning emerging technologies in Analytics, AI, and Data Science.

Key strengths:

✔ Data Analysis & Business Intelligence

✔ SQL Query Optimization & Reporting

✔ Power BI Dashboard Development

✔ Python for Analytics & Automation

✔ Data Cleaning & Transformation

✔ ETL Processes & Data Validation

✔ KPI Reporting & Performance Monitoring

✔ Predictive Analytics & Machine Learning

✔ Stakeholder Management & Communication

Open to opportunities in:

• Data Analyst

• Business Analyst

• Power BI Developer

• Business Intelligence Analyst

• Data Science Associate

• Analytics Consultant

Experience

Work history, roles, and key accomplishments

Data Scientist Intern

CodSoft

Jun 2025 - Sep 2025 (3 months)

Engineered 3+ end-to-end ML pipelines managing the full data science lifecycle from data ingestion to model deployment. Curated datasets of 5K-20K records via EDA, preprocessing, and feature engineering, reducing irrelevant features by ~30% to boost model accuracy. Trained and benchmarked 4+ classification and regression models, achieving up to 91% accuracy and F1-score of 0.89 via cross-validatio